Research on High Frequency Channel Equalization Based on Neural Network and RLS Algorithm
JIANG Honghui
WU Xiaodong
ZHU Qinghao
WANG Ruokun
Abstract：Combined artificial neural network(ANN)and recursive least square(RLS)algorithm,an improved RLS-ANN equalization algorithm is proposed to eliminate the inter-symbol interference(ISI)in high frequency signal transmission.In the use of supervised and unsupervised equalization adapted to different data segments,the amplitude and phase distortion of the high fre-quency signals can be calibrated in real time.High frequency data link(HFDL)signals are tested in data equalization,the results re-veal that compared with LMS and RLS algorithms,the proposed RLS-ANN algorithm is better at improving the convergence rate and reducing the average error of the signal constellation,as well as reducing the bit error rate of the tested signals,showing that the RLS-ANN algorithm can effectively improve the signal communication quality in in high frequency channel.
Keywords：neural networkRLS algorithmhigh frequency channel equalizationHFDL signal
Publication Date：2024-09-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 65-69 )